In 2007, approximately 200,000 lung and pancreatic cancer deaths occurred in the United States. Earlier detection with respect to progression of lung and pancreatic cancer would significantly reduce these mortality numbers. Identification of cancer biomarkers is a proven strategy for the screening and early treatment of cancer. Small amounts of peripheral blood are readily available for cancer biomarker identification and analysis. This is best exemplified by the PSA (prostate specific antigen) blood test screen for prostatic cancer. The development of biomarker blood tests to assist in the detection and diagnosis of lung and pancreatic cancers, especially in its earlier, curable, stages is imperative. Individuals with risk factors for these diseases (smoking, alcohol use, and family history) would benefit from blood tests developed for early detection of these carcinomas.
Mass spectrometry (MS) is the technical foundation of protein biomarker analysis, and its use is becoming more mandatory in cancer and disease research. Modern mass spectrometry is capable of high resolution, sensitivity, mass accuracy, and is robust in operation. Coupled with one-dimensional (1-D) or two-dimensional (2-D) gel electrophoresis, micro-HPLC, surface-enhanced templates, and various software packages, large numbers of proteins and peptides can be identified and quantified. The masses of different molecules are unique, and in order to determine the mass of that molecule, it must first be ionized. There are two ways to ionize biomolecules for mass spectrometry: laser desorption/ionization (LDI) and electrospray ionization (ESI). Once ionized, there are essentially two ways to determine mass: using a quadrupole/ion trap, and using a time-of-flight (TOF) mass analyzer. Mass spectrometry-based approaches have identified proteins specific for a number of cancers, including breast, prostate and lung cancer. Surface-enhanced laser desorption/ionication (SELDI) is an MS technique performed by coating metal grids with affinity matrices and then binding proteins/peptides from biological fluids to these surfaces followed by laser desorption and time of flight (TOF) mass determination of proteins/peptides. MALDI MS analysis (matrix-assisted laser desorption/ionization) was able to detect proteins/peptides present in control sera but absent in sera from pancreatitis/pancreatic cancer patients.
Another use of mass spectrometry in cancer and disease diagnostics is profiling of the small molecule, low mass range (approximately 500 to 5000 m/z values) of serum. This methodology, referred to as serum proteomic profiling or serum profiling, relies upon the high resolution and mass accuracy of modern mass spectrometers as well as statistical analysis software to analyze, distinguish, and classify thousands of mass peaks at once. This technology application is based upon the concept that changes in the physiological state of the human body (e.g., by disease) are reflected in changes in biomarkers present in serum. These changes could result from tissues and organs secreting and/or shedding different amounts and kinds of biomarkers and/or altered biomarkers (e.g., proteins, peptides, lipids, nucleic acids) into the circulating bloodstream. These changes could be due to duress on organ homeostasis, bodily defenses, and disease mechanisms themselves. This technology was previously used to distinguish serum mass peak patterns for breast and prostate cancer, and to develop a blood test for ovarian cancer, which, like pancreatic cancer, is very hard to diagnose in its early, curable stages
A number of previous studies have identified biomarkers in lung cancer patients using mass spectrometry as well as other approaches. One group used MALDI MS and found that serum proteins amyloid A and macrophage migration inhibitory factor were elevated in lung cancer patients (Howard et al., 2004). No distinction was made in the types of lung cancer identified, and the prognostic value of these markers was found to be limited. A more successful study was reported using SELDI MS analysis from 158 lung cancer patients and 50 controls in which a series of proteins was shown to identify non-small cell lung carcinoma 91.4% of the time (Yang et al., 2005). The analysis was not able to distinguish early stage cancer from controls. A novel approach to identify lung cancer biomarkers involves the use of breath analysis of compounds and/or their patterns uniquely exhaled by lung cancer patients. One study using this technology reported the measurement of 13 volatile organic compounds in the exhaled breath of lung cancer patients with a diagnostic accuracy of 80% (Poli et al., 2005). However, these were incapable of distinguishing types of lung cancer or identifying early stages of the disease.
A number of protein biomarkers have been identified in the sera and pancreatic juices from pancreatitis and pancreatic cancer patients. Serum biomarker protein CA-19.9 is presently used to monitor pancreatic cancer but is not useful in early diagnosis (Gattani et al., 1996). The sera and pancreatic juice of pancreatitis patients contain elevated proteases (Leto et al., 1997). Sera of pancreatic cancer patients have elevated anti-proteases (Yu et al., 2005; and Trachte et al., 2002). Phosphoglycerate kinase (PGK) was found elevated in pancreatic cancer sera (Hwang et al., 2006), and insulin-like growth factor binding protein 2 was elevated in pancreatic juice from pancreatic adenocarcinoma patients (Chen et al., 2006). The hepatocarcinoma-intestine-pancreas/pancreatitis associated protein I was identified by mass spectrometry analysis as a potential pancreatic cancer biomarker from pancreatic juice (Rosty et al., 2002). However, none of these studies were able to clearly distinguish early clinical stages of pancreatic cancer from controls.
The use of mass spectrometry (MS) to identify peptide/protein differences between sera of control and disease states holds promise in diagnostics (Richter et al., 1999). The presently disclosed and claimed invention is based on the premise that sera contain very large numbers of low molecular weight peptides and other small molecules, and this complexity will vary between disease states. The basis for this complexity likely involves exopeptidase degradation of cell proteins (Villanueva et al., 2006), and could reflect homeostatic mechanisms which change with physiological state. This results in organs/tissues shedding/secreting different amounts/kinds of biomolecules. This methodology, referred to as serum proteomic profiling or serum profiling, relies upon the high resolution and mass accuracy of modern mass spectrometers as well as bioinformatic/statistic software to be able to analyze and distinguish thousands of mass peaks. Standard statistical approaches, like those utilized in the presently disclosed and claimed invention (and described in detail herein after), are better for analysis than novel algorithms (Semmes et al., 2005). Profiling of sera and other biological fluids is presently used to catalog disease states and identify biomarker patterns in many cancers including lung/pancreatic cancer (Yang et al., 2005; and Li et al., 2002). However, for reasons given below, SELDI (surface enhanced laser desorption-ionization) MS analysis of sera has a number of problems yet the cancer biomarker field exclusively uses this technology (Sorace et al., 2003). In SELDI, sera samples are placed on affinity grids to separate peptides and proteins. Samples are then washed, ionization chemicals added, and then dried. All of these steps have the potential for artifact introduction, especially with sample crystallization which is a random process that affects the ionization step in laser desorption MS.
Presently, this emerging technology has various shortcomings, including the MS technologies and analysis techniques currently utilized. The SELDI technology involves prefractionation of sera followed by chemical addition and crystallization, and thus is a solid state analysis, which is much more difficult than an all liquid state analysis. In addition, this solid state analysis will require a much larger amount of sample than a liquid analysis would require.
Therefore, the present invention is directed to new and improved methods of identifying biomarkers in cancer or disease sera using MS techniques that overcome the defects and disadvantages of the prior art.